Database Administrator

Building the Future of Open Finance Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. The Team You will join a senior team of DBAs, SREs, and platform engineers responsible for the database and vector data platforms behind Kraken's most critical services. The group combines deep operational expertise with a platform mindset: we design systems that let engineering teams move quickly while preserving strong guarantees around performance, correctness, security, and reliability. The team is entering an important phase of evolution as Kraken continues to expand globally and as AI-enabled product and internal platform use cases grow. Over the next year, we are focused on strengthening PostgreSQL operational excellence, building reliable vector data capabilities, preparing for significant future scale, and increasing automation and self-service so database operations become safer and more efficient at scale. This is not a traditional keep-the-lights-on DBA team. Our work centers on scaling high-throughput PostgreSQL environments, operating vector search and embedding stores with production discipline, shaping reliable patterns for high-traffic systems, and transforming operational knowledge into automated, auditable workflows that uplift the engineering organization. The Opportunity - Scale and tune high-throughput PostgreSQL clusters that support continued global expansion and new product initiatives. - Own PostgreSQL reliability fundamentals: WAL behavior, checkpoints, autovacuum, query planning, locking, replication lag, backup/restore, and capacity planning. - Help build and operate vector data capabilities, including pgvector and dedicated VectorDB platforms where appropriate. - Define production patterns for embeddings, approximate nearest neighbor indexes, metadata filtering, recall/latency tradeoffs, reindexing, data freshness, and drift management. - Strengthen high-availability, disaster-recovery, PITR, and backup approaches through sound design and regularly validated procedures. - Reduce manual operational work by building automation, improving process consistency, and enabling safe, low-friction database workflows. - Improve observability and alert quality by championing meaningful metrics, reducing noise, and ensuring operational clarity across PostgreSQL and vector workloads. - Enhance database security through robust access controls, disciplined patching and upgrade practices, encryption, auditability, and secure operational patterns. - Contribute to modern platform initiatives, including containerized environments, infrastructure-as-code workflows, GitOps, reproducible deployments, and self-service database operations. - Partner with service, AI, and platform teams to drive better performance patterns, operational readiness, data hygiene, and safe use of vector search across the engineering organization. - Participate in on-call rotations with a long-term focus on making on-call predictable, well-instrumented, and shaped by preventative engineering. What You Bring - 5+ years operating PostgreSQL in high-volume production environments, including performance tuning, replication, backup/restore, upgrades, and incident troubleshooting. - Strong understanding of PostgreSQL internals and operations: MVCC, transaction isolation, locks, WAL, checkpoints, autovacuum, bloat, statistics, query planner behavior, partitioning, and index strategy. - Hands-on experience with high availability and read scaling: streaming replication, replication slots, failover, lag management, PITR, backups, and disaster-recovery drills. - Experience with connection pooling and traffic management for PostgreSQL, especially PgBouncer, HAProxy, Kubernetes service routing, or comparable patterns. - Practical VectorDB or vector search experience, such as pgvector, Qdrant, Milvus, Weaviate, OpenSearch vector search, or similar systems. - Ability to reason about vector index types and operational tradeoffs, including HNSW/IVFFlat-style indexes, recall, latency, memory, ingestion throughput, metadata filters, rebuilds, and versioned embeddings. - Practical experience with CI/CD, GitOps, and Infrastructure-as-Code workflows. Terraform experience is ideal. - Solid cloud, Linux, storage, and networking fundamentals. - Experience with containers and orchestration platforms, including building container images and managing Kubernetes workloads at scale. - Strong security instincts around access control, credential lifecycle, encryption, auditability, upgrade processes, and safe operational workflows. - Observability expertise: monitoring, alerting hygiene, SLOs, dashboards, query-level visibility, and readiness for incident response. - Strong communication and collaboration skills with the ability to partner with stakeholders, negotiate long-term plans, write formal documentation, and tie success to specific metrics and KPIs. Nice to haves - Experience with SRE methodologies such as error budgets, operational reviews, reliability programs, and failure exercises. - Strong scripting or programming ability, preferably Python, Go, or Rust, used to build automation and internal tools. - Hands-on experience with GitOps tooling such as ArgoCD, GitHub Actions, or GitLab CI. - Exposure to multi-region, multi-datacenter, or active/passive disaster-recovery designs. - Experience supporting AI, retrieval, personalization, fraud, search, or recommendation systems that depend on embeddings or hybrid search. - Interest in cryptocurrency or decentralized systems.